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Physically Unclonable Functions (PUFs) translate unavoidable variations in certain parameters of materials, waves, or devices into random and unique signals. They have found many applications in the Internet of Things (IoT), authentication systems, FPGA industry, several other areas in communications and related technologies, and many commercial products. Statistical Trend Analysis of Physically Unclonable Functions first presents a review on cryptographic hardware and hardware-assisted cryptography. The review highlights PUF as a mega trend in research on cryptographic hardware design. Afterwards, the authors present a combined survey and research work on PUFs using a systematic approach. As part of the survey aspect, a state-of-the-art analysis is presented as well as a taxonomy on PUFs, a life cycle, and an established ecosystem for the technology. In another part of the survey, the evolutionary history of PUFs is examined, and strategies for further research in this area are suggested. In the research side, this book presents a novel approach for trend analysis that can be applied to any technology or research area. In this method, a text mining tool is used which extracts 1020 keywords from the titles of the sample papers. Then, a classifying tool classifies the keywords into 295 meaningful research topics. The popularity of each topic is then numerically measured and analyzed over the course of time through a statistical analysis on the number of research papers related to the topic as well as the number of their citations. The authors identify the most popular topics in four different domains; over the history of PUFs, during the recent years, in top conferences, and in top journals. The results are used to present an evolution study as well as a trend analysis and develop a roadmap for future research in this area. This method gives an automatic popularity-based statistical trend analysis which eliminates the need for passing personal judgments about the direction of trends, and provides concrete evidence to the future direction of research on PUFs. Another advantage of this method is the possibility of studying a whole lot of existing research works (more than 700 in this book). This book will appeal to researchers in text mining, cryptography, hardware security, and IoT.
This book studies the intersection between cryptography and AI, highlighting the significant cross-impact and potential between the two technologies. The authors first study the individual ecosystems of cryptography and AI to show the omnipresence of each technology in the ecosystem of the other one. Next, they show how these technologies have come together in collaborative or adversarial ways. In the next section, the authors highlight the coevolution being formed between cryptography and AI. Throughout the book, the authors use evidence from state-of-the-art research to look ahead at the future of the crypto-AI dichotomy. The authors explain how they anticipate that quantum computing will join the dichotomy in near future, augmenting it to a trichotomy. They verify this through two case studies highlighting another scenario wherein crypto, AI and quantum converge. The authors study current trends in chaotic image encryption as well as information-theoretic cryptography and show how these trends lean towards quantum-inspired artificial intelligence (QiAI). After concluding the discussions, the authors suggest future research for interested researchers.
The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. - Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques - Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques
This book provides the foundations for understanding hardware security and trust, which have become major concerns for national security over the past decade. Coverage includes security and trust issues in all types of electronic devices and systems such as ASICs, COTS, FPGAs, microprocessors/DSPs, and embedded systems. This serves as an invaluable reference to the state-of-the-art research that is of critical significance to the security of, and trust in, modern society’s microelectronic-supported infrastructures.
Physically unclonable functions (PUFs) are innovative physical security primitives that produce unclonable and inherent instance-specific measurements of physical objects; in many ways they are the inanimate equivalent of biometrics for human beings. Since they are able to securely generate and store secrets, they allow us to bootstrap the physical implementation of an information security system. In this book the author discusses PUFs in all their facets: the multitude of their physical constructions, the algorithmic and physical properties which describe them, and the techniques required to deploy them in security applications. The author first presents an extensive overview and classification of PUF constructions, with a focus on so-called intrinsic PUFs. He identifies subclasses, implementation properties, and design techniques used to amplify submicroscopic physical distinctions into observable digital response vectors. He lists the useful qualities attributed to PUFs and captures them in descriptive definitions, identifying the truly PUF-defining properties in the process, and he also presents the details of a formal framework for deploying PUFs and similar physical primitives in cryptographic reductions. The author then describes a silicon test platform carrying different intrinsic PUF structures which was used to objectively compare their reliability, uniqueness, and unpredictability based on experimental data. In the final chapters, the author explains techniques for PUF-based entity identification, entity authentication, and secure key generation. He proposes practical schemes that implement these techniques, and derives and calculates measures for assessing different PUF constructions in these applications based on the quality of their response statistics. Finally, he presents a fully functional prototype implementation of a PUF-based cryptographic key generator, demonstrating the full benefit of using PUFs and the efficiency of the processing techniques described. This is a suitable introduction and reference for security researchers and engineers, and graduate students in information security and cryptography.
This book discusses the design principles of physically unclonable functions (PUFs) and how these can be employed in hardware-based security applications, in particular, the book provides readers with a comprehensive overview of security threats and existing countermeasures. This book has many features that make it a unique source for students, engineers and educators, including more than 80 problems and worked exercises, in addition to, approximately 200 references, which give extensive direction for further reading.
This book constitutes revised selected papers from the 8th International Workshop on Constructive Side-Channel Analysis and Secure Design, COSADE 2017, held in Paris, France, in April 2017. The 17 papers presented in this volume were carefully reviewed and selected from numerous submissions. They were organized in topical sections named: Side-Channel Attacks and Technological Effects; Side-Channel Countermeasures; Algorithmic Aspects in Side-Channel Attacks; Side-Channel Attacks; Fault Attacks; Embedded Security; and Side-Channel Tools.
This book provides a valuable reference for digital forensics practitioners and cyber security experts operating in various fields of law enforcement, incident response and commerce. It is also aimed at researchers seeking to obtain a more profound knowledge of Digital Forensics and Cybercrime. Furthermore, the book is an exceptional advanced text for PhD and Master degree programmes in Digital Forensics and Cyber Security. Each chapter of this book is written by an internationally-renowned expert who has extensive experience in law enforcement, industry and academia. The increasing popularity in the use of IoT devices for criminal activities means that there is a maturing discipline and industry around IoT forensics. As technology becomes cheaper and easier to deploy in an increased number of discrete, everyday objects, scope for the automated creation of personalised digital footprints becomes greater. Devices which are presently included within the Internet of Things (IoT) umbrella have a massive potential to enable and shape the way that humans interact and achieve objectives. These also forge a trail of data that can be used to triangulate and identify individuals and their actions. As such, interest and developments in autonomous vehicles, unmanned drones and ‘smart’ home appliances are creating unprecedented opportunities for the research communities to investigate the production and evaluation of evidence through the discipline of digital forensics.
Recently, the internet of things (IoT) has brought the vision of a smarter world into reality with a massive amount of data and numerous services. With the outbreak of the COVID-19 pandemic, artificial intelligence (AI) has gained significant attention by utilizing its machine learning algorithms for quality patient care. The integration of IoT with AI may open new possibilities for both technologies and can play a big part in smart healthcare by providing improved insight into healthcare data and allowing for more inexpensive personalized care. The Handbook of Research on Advancements in AI and IoT Convergence Technologies considers recent advancements in AI and IoT convergence technologies with a focus on state-of-the-art approaches, methodologies, and systems for the design, development, deployment, and innovative use of those convergence technologies. It also provides insight into how to develop AI and IoT convergence techniques to meet industrial demands and covers the emerging research topics that are going to define the future of AI and IoT convergence technology development. Covering key topics such as diseases, smart healthcare, social distance monitoring, and security, this major reference work is ideal for industry professionals, nurses, healthcare workers, computer scientists, policymakers, researchers, scholars, practitioners, instructors, and students.
Even though blockchain technology was originally created as a ledger system for bitcoin to operate on, using it for areas other than cryptocurrency has become increasingly popular as of late. The transparency and security provided by blockchain technology is challenging innovation in a variety of businesses and is being applied in fields that include accounting and finance, supply chain management, and education. With the ability to perform such tasks as tracking fraud and securing the distribution of medical records, this technology is key to the advancement of many industries. The Research Anthology on Blockchain Technology in Business, Healthcare, Education, and Government is a vital reference source that examines the latest scholarly material on trends, techniques, and uses of blockchain technology applications in a variety of industries, and how this technology can further transparency and security. Highlighting a range of topics such as cryptography, smart contracts, and decentralized blockchain, this multi-volume book is ideally designed for academics, researchers, industry leaders, managers, healthcare professionals, IT consultants, engineers, programmers, practitioners, government officials, policymakers, and students.